Development and Validation of Prediction Models for Exacerbation, Frequent Exacerbations and Severe Exacerbations of Chronic Obstructive Pulmonary Disease: A Registry Study in North China.

Abstract

In COPD patients, exacerbation has a detrimental influence on the quality of life, disease progression and socioeconomic burden. This study aimed to develop and validate models to predict exacerbation, frequent exacerbations and severe exacerbations in COPD patients. We conducted an observational prospective multicenter study. Clinical data of all outpatients with stable COPD were collected from Beijing Chaoyang Hospital and Beijing Renhe Hospital between January 2018 and December 2019. Patients were followed up for 1 year. The data from Chaoyang Hospital was used for modeling dataset, and that of Renhe Hospital was used for external validation dataset. The final dataset included 456 patients, with 326 patients as the model group and 130 patients as the validation group. Using LABA + ICS, frequent exacerbations in the past year and CAT score were independent risk factors for exacerbation in the next year (OR = 2.307, 2.722 and 1.147), and FVC %pred as a protective factor (OR = 0.975). Combined with chronic heart failure, frequent exacerbations in the past year, blood EOS counts and CAT score were independent risk factors for frequent exacerbations in the next year (OR = 4.818, 2.602, 1.015 and 1.342). Using LABA + ICS, combined with chronic heart failure, frequent exacerbations in the past year and CAT score were independent risk factors for severe exacerbations in the next year (OR = 1.950, 3.135, 2.980 and 1.133). Based on these prognostic models, nomograms were generated. The prediction models were simple and useful tools for predicting the risk of exacerbation, frequent exacerbations and severe exacerbations of COPD patients in North China.